Phase Recovery, MaxCut and Complex Semidefinite Programming
Optimization and Control
2013-07-23 v3
Abstract
Phase retrieval seeks to recover a signal x from the amplitude |Ax| of linear measurements. We cast the phase retrieval problem as a non-convex quadratic program over a complex phase vector and formulate a tractable relaxation (called PhaseCut) similar to the classical MaxCut semidefinite program. We solve this problem using a provably convergent block coordinate descent algorithm whose structure is similar to that of the original greedy algorithm in Gerchberg-Saxton, where each iteration is a matrix vector product. Numerical results show the performance of this approach over three different phase retrieval problems, in comparison with greedy phase retrieval algorithms and matrix completion formulations.
Cite
@article{arxiv.1206.0102,
title = {Phase Recovery, MaxCut and Complex Semidefinite Programming},
author = {Irène Waldspurger and Alexandre d'Aspremont and Stéphane Mallat},
journal= {arXiv preprint arXiv:1206.0102},
year = {2013}
}
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